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Housing in the natural city: The role of prefabrication

2004· article· en· W4205989895 on OpenAlexaboutno aff
Mark Gorgolewski

Bibliographic record

VenueEkistics and the new habitat · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicArchitecture and Cultural Influences
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityCertificationPrivate sectorEnvironmental designLibrary scienceEngineeringManagementPolitical sciencePublic administrationSociologyArchitectural engineeringCivil engineeringLawComputer science

Abstract

fetched live from OpenAlex

The author is a graduate of University College, London, Cranfield University and Oxford Brookes University in the UK where he completed his Ph. D thesis about Energy Efficient Housing. He is a registered architect in the UK and has worked for many years as an environmental consultant to the construction industry. In 2003, Dr Gorgolewski moved to Canada to take up a position as Associate Professor at the School of Architectural Science at Ryerson University where he lectures on issues of sustainability, environmental design and building science. Dr Gorgolewski has published several books and many articles and papers on issues of sustainable construction. His past positions include chair of the committee of the Association for Environment Conscious Building, in the UK, secretary to the Steel Sector Committee for Sustainable Construction and member of the Building Research Establishment Certification Technical Board. He has received many grants from public and private institutions to investigate issues of sustainable construction. Currently he is pursuing research in the areas of office building design in the 21st century and the benefits of thermal mass. The text that follows is an edited and revised version of a paper presented at the international symposion on "The Natural City, " Toronto, 23-25 June, 2004, sponsored by the University of Toronto's Division of the Environment, Institute for Environmental Studies, and the World Society for Ekistics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.216
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2004
Admission routes1
Has abstractyes

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